Provide sUAS traffic analysis – sUAS News – The drone case
For the FAA to maintain NAS security and adapt to new types of UAS operations, it is important to monitor the effectiveness of existing UAS regulations and anticipate future UAS integration needs. Using first-of-its-kind sensing data, this research will provide data to address these needs by analyzing sUAS traffic at multiple urban locations across the NAS.
The initial annual report presents the progress, conclusions and preliminary observations on the research tasks completed during the first of the three years of execution. With the growth of sUAS operations in the National Airspace System (NAS), there is a demonstrated need to identify and report these activities objectively and empirically. The current study aims to establish a framework to address this need to perform sUAS traffic analysis in low-level airspace. The collection and analysis of this empirical data is used to inform the Federal Aviation Administration (FAA) in several critical areas: (1) identify, assess, and monitor sUAS safety risks; (2) determine the effectiveness of existing sUAS regulations; (3) accurately predict sUAS traffic levels; and (4) help identify and assess future risks to aviation.
To answer the project’s research questions, the researchers established six focus areas to functionally allocate effort. The tasks are: (A) Development of analysis tools and literature review, (B) Current status of sUAS traffic within the NAS, (C) Compliance and exceedance of 14 CFR§107 operational limits, (D ) sUAS operations near an airfield and risks encountered with manned air traffic, (E) forecasting industry growth and potential implications of advanced air mobility, and (F) communicating the results. Through these different missions, the team provides clear answers to the research questions posed in this study.
Data for this research was collected through a nationwide deployment of Unmanned Aircraft System (UAS) detection equipment through collaboration with two companies. The collaboration with these partners provides 166 UAS detection sensors deployed in 64 diverse geographical areas. This instrumentation performs continuous, passive monitoring of detailed operational data such as identification (electronic serial number), location, altitude, speed, and location of the remote pilot. The data is collected for sUAS vehicles manufactured by DJI, and their market share is estimated at around 76% based on sales volume, indicating that the system will detect a high proportion of sUAS operations.
To facilitate streamlined data collection and processing, the project partnered with Unmanned Systems Robotics Analysis, Inc. (URSA). The team produces customizable analytics and reports to synthesize data received from multiple sources through the use of URSA’s UAS & Counter-UAS Analytics Platform (UCAP). This tool leverages modern data science and artificial intelligence (AI) capabilities to provide rapid pattern detection, data visualization, and automated reporting capabilities.
Preliminary data yielded several insights into sUAS operations. Through initial data analysis, the research team assessed operations in several key areas, including sUAS flights by location, airspace utilization, seasonal variations in operations (including holiday peaks in operations), time of day, operations by type of sUAS, maximum number of sUAS flight altitudes, proximity of operations to airports, sUAS launch locations, rates withdrawal/abandonment of sUAS and estimated registration compliance. The research team also evaluated a comparison of empirical data with observational reports.
In addition, the team evaluated and estimated compliance and exceedances of 14 CFR §107, including operations from a moving vehicle, daytime operations exceedance, aircraft operations beyond line of sight, operations near and around other aircraft, operations over people/large gatherings, speed and altitude limitations, visibility and cloud clearance, probability of encounter in flight and the effectiveness of the Low Altitude Clearance and Notification Capability (LAANC) system.
The initial annual report provides a detailed analysis of these critical research areas. However, in general, some preliminary conclusions can be summarized. First, clear patterns emerge in sUAS operations based on seasonal and time-of-day variations. Second, sUAS operations appear, for the most part, to comply with regulations for operations near airports. Third, sUAS withdrawal/discontinuation rates appear to be high, especially after the first 3-4 months of use. Finally, in general, early results indicate that most sUAS operations are flying in accordance with 14 CFR §107 regulations. The report examines these results in detail, along with the supporting data. Although these findings are preliminary, the results inform the FAA about the types and patterns of sUAS operations in the NAS. This data informs future decisions, policies and procedures for the integration of unmanned and manned operations.